دورية أكاديمية
Fitting the data from embryo implantation prediction: Learning from label proportions
| العنوان: | Fitting the data from embryo implantation prediction: Learning from label proportions |
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| المؤلفون: | Hernández-González, J., Inza, I., Crisol-Ortíz, L., Guembe, M.A., Iñarra, M.J., Lozano, J.A. |
| سنة النشر: | 2016 |
| المجموعة: | BIRD - BCAM's Institutional Repository Data (Basque Center for Applied Mathematics) |
| مصطلحات موضوعية: | Assisted reproductive technologies, embryo selection, machine learning, learning from label proportions, Bayesian network models |
| الوصف: | Machine learning techniques have been previously used to assist clinicians to select embryos for human-assisted reproduction. This work aims to show how an appropriate modeling of the problem can contribute to improve machine learning techniques for embryo selection. In this study, a dataset of 330 consecutive cycles (and associated embryos) carried out by the Unit of Assisted Reproduction of the Hospital Donostia (Spain) throughout 18 months has been analyzed. The problem of the embryo selection has been modeled by a novel weakly supervised paradigm, learning from label proportions, which considers all the available data, including embryos whose fate cannot be certainly established. Furthermore, all the collected features, describing cycles and embryos, have been considered in a multi-variate data analysis. Our integral solution has been successfully tested. Experimental results show that the proposed technique consistently outperforms an equivalent approach based on standard supervised classification. Embryos in this study were selected for transference according to the criteria of the Spanish Association for Reproduction Biology Studies. Obtained classification models outperform these criteria, specifically reordering medium-quality embryos. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 0962-2802 |
| العلاقة: | http://smm.sagepub.com/content/early/2016/05/27/0962280216651098.abstractTest; http://hdl.handle.net/20.500.11824/138Test |
| DOI: | 10.1177/0962280216651098 |
| الإتاحة: | https://doi.org/20.500.11824/138Test https://doi.org/10.1177/0962280216651098Test https://hdl.handle.net/20.500.11824/138Test |
| حقوق: | Reconocimiento-NoComercial-CompartirIgual 3.0 España ; http://creativecommons.org/licenses/by-nc-sa/3.0/esTest/ ; info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.4CC203F5 |
| قاعدة البيانات: | BASE |
| تدمد: | 09622802 |
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| DOI: | 10.1177/0962280216651098 |